[A version of this post appears on the O'Reilly Radar.]The O’Reilly Data Show Podcast: Robert Nishihara and Philipp Moritz on a new framework for reinforcement learning and AI applications.Subscribe to the O’Reilly Data Show Podcast to explore the opportunities and techniques driving big data, data science, and AI. Find us on Stitcher, TuneIn, iTunes, SoundCloud, RSS.In this episode of the Data Show, I spoke with Robert Nishihara and Philipp Moritz, graduate students at UC Berkeley and members of RISE Lab. I wanted to get an update on Ray, an open source distributed execution framework that...

[A version of this post appears on the O'Reilly Radar.]A look ahead at the tools and methods for learning from sparse feedback.As more companies begin to experiment with and deploy machine learning in different settings, it’s good to look ahead at what future systems might look like. Today, the typical sequence is to gather data, learn some underlying structure, and deploy an algorithm that systematically captures what you’ve learned. Gathering, preparing, and enriching the right data—particularly training data—is essential and remains a key bottleneck among companies wanting to use machine...

[A version of this post appears on the O'Reilly Radar.]The O’Reilly Data Show Podcast: Soumith Chintala on building a worthy successor to Torch and deep learning within Facebook.Subscribe to the O'Reilly Data Show Podcast to explore the opportunities and techniques driving big data, data science, and AI. Find us on Stitcher, TuneIn, iTunes, SoundCloud, RSS.In this episode of the Data Show, I spoke with Soumith Chintala, AI research engineer at Facebook. Among his many research projects, Chintala was part of the team behind DCGAN (Deep Convolutional Generative Adversarial Networks), a widely...

(15 days ago)

About:

I am a Senior Researcher in the Market Research Group at O'Reilly Media, Inc., founder of Verisi Data Studio, and an advisor to Yakit. I have applied Business Intelligence, Data Mining and Statistical Analysis in a variety of domains including Financial Engineering, Direct Marketing, Consumer and Market Research, Targeted Advertising, and Text Mining. My background includes stints with an investment management company, internet startups, and financial services. At O'Reilly, I work on custom research and consulting projects, involving all aspects of data intelligence: data acquisition, data transformation and management, analytics, and visualization. In the process, I help companies understand developments in a wide-range of emerging technology topics, including social media, (mobile) application platforms, big data and analytics, and frugal innovation. I remain interested in Quantitative Finance and my musings can be found on my blog The Practical Quant.

An ex-academic, I was an Assistant Professor at U.C. Davis and was the founding Department Chair for Statistics and Mathematics at C.S.U. Monterey Bay. I have been a visiting member of the Mathematical Sciences Research Institute in Berkeley and have taught at U.C. Santa Barbara and the University of the Philippines. I enjoy writing and have written and published on topics ranging from Applied Mathematics and Statistics, Finance, Marketing Research, and Technology.